Moving sensors for improved estimation of dynamic structures: Experimental validation

被引:1
|
作者
Chierichetti, Maria [1 ]
Demetriou, Michael [2 ]
机构
[1] San Jose State Univ, 1 Washington Sq, San Jose, CA 95112 USA
[2] Worcester Polytech Inst, Mech Engn Dept, Worcester, MA 01609 USA
关键词
State observer; dynamic structures; system identification; monitoring; natural observer; mobile sensors;
D O I
10.1177/1077546320965014
中图分类号
O42 [声学];
学科分类号
070206 ; 082403 ;
摘要
In the monitoring of structural systems, the use of multiple high-end sensors may prove to be economically prohibitive. The alternative approach would be to use fewer devices capable of moving across the span of the structural system. In the proposed approach, a velocity sensor that is able to move across the spatial domain and obtain point-wise velocity measurements is combined to a novel dynamic observer. Based on the measured velocities, a state estimator is developed, the gain of which depends on the motion of the sensor. The motion of the sensor is defined using Lyapunov redesign methods and depends only on the estimation error at the current sensor position. The guidance policy is performance based and steers the sensor to spatial regions of the structure with larger estimation errors. The proposed approach is validated with a one-dimensional flexible structure, mathematically described by an Euler-Bernoulli partial differential equation. The moving sensor is realized through the use of a laser scanning vibrometer that provides both the moving measurements and additional measurements against which the proposed approach will be validated. Once measurements over a large number of locations are acquired, the experimental results are fed to the algorithm that selects the instantaneous sensor location. Experimental results for linear and nonlinear beam cases are presented to show the feasibility and robustness of the proposed approach.
引用
收藏
页码:2701 / 2710
页数:10
相关论文
共 50 条
  • [41] New improved FLANN approach for dynamic modelling of sensors
    Huang, Song-ling
    Hao, Kuan-sheng
    Zhao, Wei
    INTERNATIONAL JOURNAL OF COMPUTER APPLICATIONS IN TECHNOLOGY, 2011, 41 (1-2) : 4 - 10
  • [42] A dynamic ALE formulation for structures under moving loads
    Anantheswar, Atul
    Wollny, Ines
    Kaliske, Michael
    COMPUTATIONAL MECHANICS, 2024, 73 (01) : 139 - 157
  • [43] Experimental validation of a numerical code by thin film heat flux sensors for the resolution of thermal bridges in dynamic conditions
    Ascione, Fabrizio
    Bianco, Nicola
    De Masi, Rosa Francesca
    Mauro, Gerardo Maria
    Musto, Marilena
    Vanoli, Giuseppe Peter
    APPLIED ENERGY, 2014, 124 : 213 - 222
  • [44] Estimation and validation of semiparametric dynamic nonlinear models
    Rolain, Yves
    Van Moer, Wendy
    Schoukens, Johan
    Dhaene, Tom
    IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT, 2008, 57 (02) : 395 - 400
  • [45] DYNAMIC BEHAVIOR OF BEAM STRUCTURES CARRYING MOVING MASSES
    SAIGAL, S
    JOURNAL OF APPLIED MECHANICS-TRANSACTIONS OF THE ASME, 1986, 53 (01): : 222 - 224
  • [46] A dynamic ALE formulation for structures under moving loads
    Atul Anantheswar
    Ines Wollny
    Michael Kaliske
    Computational Mechanics, 2024, 73 : 139 - 157
  • [47] Detection of moving objects using thermal imaging sensors for occupancy estimation
    Chidurala, Veena
    Li, Xinrong
    INTERNET OF THINGS, 2022, 17
  • [48] Lifetime Estimation of Events from Dynamic Vision Sensors
    Mueggler, Elias
    Forster, Christian
    Baumli, Nathan
    Gallego, Guillermo
    Scaramuzza, Davide
    2015 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION (ICRA), 2015, : 4874 - 4881
  • [49] Signal estimation and system identification with nonlinear dynamic sensors
    Berberich, Julian
    Sznaier, Mario
    Allgoewer, Frank
    2019 3RD IEEE CONFERENCE ON CONTROL TECHNOLOGY AND APPLICATIONS (IEEE CCTA 2019), 2019, : 538 - 543
  • [50] Dynamic matching error of stress sensors in concrete structures
    Xue, Chao -yang
    Kong, De-ren
    Li, Bo
    Xu, Chun-dong
    MEASUREMENT, 2024, 224